"A protein language model for exploring viral fitness landscapes"
Nature Communications Online 13 May 2025 doi:10.1038/s41467-025-59422-w
CoVFit: An AI-Powered Framework to Predict the Evolutionary Fitness of SARS-CoV-2 Variants
Description
Published Article
Jumpei Ito1,2, Adam Strange1, Wei Liu1,3,4, Gustav Joas1,5,
Spyros Lytras1,6, The Genotype to Phenotype Japan (G2P-Japan) Consortium, and Kei Sato1,2,6,7
1Department of Microbiology and Immunology, The University of Tokyo, Tokyo, Japan
2International Research Center for Infectious Diseases, The University of Tokyo, Tokyo, Japan
3Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland
4Swiss Institute of Bioinformatics, Geneva, Switzerland
5Department of Medicine, Karolinska Institutet, Stockholm, Sweden
6Centre for Virus Research, University of Glasgow, Glasgow, UK
7International Vaccine Design Center, The University of Tokyo, Tokyo, Japan
Spyros Lytras1,6, The Genotype to Phenotype Japan (G2P-Japan) Consortium, and Kei Sato1,2,6,7
1Department of Microbiology and Immunology, The University of Tokyo, Tokyo, Japan
2International Research Center for Infectious Diseases, The University of Tokyo, Tokyo, Japan
3Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland
4Swiss Institute of Bioinformatics, Geneva, Switzerland
5Department of Medicine, Karolinska Institutet, Stockholm, Sweden
6Centre for Virus Research, University of Glasgow, Glasgow, UK
7International Vaccine Design Center, The University of Tokyo, Tokyo, Japan
